New Ways of Working
Lecture 1
Debate on new ways of working
- who is responsible when automation goes wrong? to what extend we want
technology to make decisions for us Europe should not join the AI
acceleration
- Very optimistic, rise in employment
● Dataism
Dataism is the belief that the authority of Big Data and algorithms effectively
transforms all political and social structures into data-processing systems based on
real-time tracking and predictive analysis
- Ex: A fully data-driven society where privacy diminishes, a dependence on
technology, and a powerful elite controlling information and resources (elite
technocrats).
- EX: the China Social Credit System exemplifies how algorithms and Big
Data reshape societal governance. It uses real-time tracking (e.g.,
surveillance and financial data) and predictive analysis to assign "social
credit scores" based on individual behavior. These scores influence access to
services, travel, and opportunities, promoting compliance with societal norms.
This system demonstrates the shift from traditional governance to data-driven
decision-making, raising ethical concerns about privacy, freedom, and human
agency.
● Exterminism
The rich monopolize all the resources while the earth burns, in the process
eliminating all people who produce little or no economic value (Frase, 2016)
surrounded by an increasing ecological and economic crisis.
- Ex: Climate change and ecological disasters, an increased risk of war,
growing economic inequality
● Re/Upskilling
,The need for continuous re-training in response to the obsolescence of existing skills
(reskilling), or the necessity to learn entirely new skills (upskilling) in adaptation to
changing demands (Schlogl, Weiss & Prainsack, 2021)
- The need for continuous skill development (reskilling) and acquiring
entirely new skills (upskilling) to keep up with evolving technology.
- Ex: Workers needing to keep up with new technologies, partial automation (of
tasks), the emergence of new types of jobs and industries, humans learning to
collaborate with robots
● Augmentation
Computers (algorithms) and humans working together, by design, to enhance one
another, such that the intelligence of the resulting system improves
- Ex: Algorithms making human work faster and easier, increased productivity,
technology enhancing rather than replacing human labor
● Singularity
Artificial intelligence (AI) surpassing human intelligence, as a result of exponential
growth in the technology leading up to a “point of no return”
- Ex: Intelligent machines surpassing human capacities in every way, full
automation (of jobs), humanity entering a new historical era.
● Job Destruction
The mass unemployment of workers in many industries as a result of automation
and structural shifts in the labor market (Frey & Osborne, 2013)
- Ex: The disappearance of jobs and industries (that are not compensated for
by new job creation), mass unemployment
● Work De-Intensification
The opposite of the historical phenomenon of work intensification (Le Fevre, Boxall &
Macky, 2015)— that is, a decrease in the need for human labor and long work hours,
calling into question the role of work in human life and work as a primary source of
income (Bregman, 2017)
- Ex: more leisure, time for side-gigs and craftwork, and the introduction of a
universal basic income.
,Actors in the Public Debate
Different groups play key roles in pushing these narratives:
1. Tech/Innovation Experts: Promote technology and its benefits (e.g., automation,
augmentation, work de-intensification).
2. Authors/Journalists: Frame narratives to inform or provoke debate, worrying tech
would hurt society (exterminism and job destruction), .
3. Economy/Labor Market Experts: Highlight economic impacts like job loss or
re-upskilling needs, job destruction. Humans can adapt to new jobs.
4. Policymakers/Public Administrators: Propose regulations and policies to
manage these changes.
5. Engaged Citizens: React to narratives, often voicing concerns (e.g., loss of
privacy, inequality).
These Narratives Matter
● Political Nature: Narratives are not neutral predictions; they reflect political and
ideological struggles over what the future should look like.
● Influence on Reality: Dominant narratives influence societal actions and policies,
shaping the future (e.g., funding for upskilling programs).
● Second-Order Chaos: Predictions about the future influence the outcome itself.
○ Example: If people believe AI will replace jobs, it can accelerate decisions to automate.
The truth is not out there: An enacted view of the digital economy. In:
Understanding the digital economy: Data, tools, and research. Orlikowski, W.
J., & Iacono, C. S. (2000).
3 approaches
1. Technological determinism
2. Strategic choice
3. Enacted view
1. Technological Determinism
, Technology is a neutral, exogenous (dıştan kaynaklı) force that exerts unidirectional
and causal influences over humans and organizations. Similar to those operating in
nature.
Tech is an object that influences organizational outcomes such as: increasing
productivity, expanding collaboration, leading decentralization…
2. Strategic Choice
Managers decide which technologies they will adopt through strategic alignment of
the tech with the organization. This choice determines the outcome, not the tech
itself.
Managers rather than users are the key actors in shaping technology to a
particular organizational or economic end.
3. Enacted View
Ongoing technological production: tech is center stage.
Outcomes emerge from our situated actions (practices), and collective actions,
Recognize the social and unpredictable nature of technological use.
3 implications
- tech is social, dynamic, and multiple
- tech must be used to have an effect
- use of tech has unintended consequences
(Volti 2012) Professionals and professionlization
This paper, titled "Professions and Professionalization" by Rudi Volti (2012),
discusses the distinct characteristics of professions, how they differ from other
occupations, and the process of professionalization.
Key Points:
1. Definition of a Profession: A profession is marked by specialized
knowledge, formal education, and adherence to ethical standards.
Professions such as medicine and law hold a higher status compared to other
occupations because of their unique roles and responsibilities in society.
Lecture 1
Debate on new ways of working
- who is responsible when automation goes wrong? to what extend we want
technology to make decisions for us Europe should not join the AI
acceleration
- Very optimistic, rise in employment
● Dataism
Dataism is the belief that the authority of Big Data and algorithms effectively
transforms all political and social structures into data-processing systems based on
real-time tracking and predictive analysis
- Ex: A fully data-driven society where privacy diminishes, a dependence on
technology, and a powerful elite controlling information and resources (elite
technocrats).
- EX: the China Social Credit System exemplifies how algorithms and Big
Data reshape societal governance. It uses real-time tracking (e.g.,
surveillance and financial data) and predictive analysis to assign "social
credit scores" based on individual behavior. These scores influence access to
services, travel, and opportunities, promoting compliance with societal norms.
This system demonstrates the shift from traditional governance to data-driven
decision-making, raising ethical concerns about privacy, freedom, and human
agency.
● Exterminism
The rich monopolize all the resources while the earth burns, in the process
eliminating all people who produce little or no economic value (Frase, 2016)
surrounded by an increasing ecological and economic crisis.
- Ex: Climate change and ecological disasters, an increased risk of war,
growing economic inequality
● Re/Upskilling
,The need for continuous re-training in response to the obsolescence of existing skills
(reskilling), or the necessity to learn entirely new skills (upskilling) in adaptation to
changing demands (Schlogl, Weiss & Prainsack, 2021)
- The need for continuous skill development (reskilling) and acquiring
entirely new skills (upskilling) to keep up with evolving technology.
- Ex: Workers needing to keep up with new technologies, partial automation (of
tasks), the emergence of new types of jobs and industries, humans learning to
collaborate with robots
● Augmentation
Computers (algorithms) and humans working together, by design, to enhance one
another, such that the intelligence of the resulting system improves
- Ex: Algorithms making human work faster and easier, increased productivity,
technology enhancing rather than replacing human labor
● Singularity
Artificial intelligence (AI) surpassing human intelligence, as a result of exponential
growth in the technology leading up to a “point of no return”
- Ex: Intelligent machines surpassing human capacities in every way, full
automation (of jobs), humanity entering a new historical era.
● Job Destruction
The mass unemployment of workers in many industries as a result of automation
and structural shifts in the labor market (Frey & Osborne, 2013)
- Ex: The disappearance of jobs and industries (that are not compensated for
by new job creation), mass unemployment
● Work De-Intensification
The opposite of the historical phenomenon of work intensification (Le Fevre, Boxall &
Macky, 2015)— that is, a decrease in the need for human labor and long work hours,
calling into question the role of work in human life and work as a primary source of
income (Bregman, 2017)
- Ex: more leisure, time for side-gigs and craftwork, and the introduction of a
universal basic income.
,Actors in the Public Debate
Different groups play key roles in pushing these narratives:
1. Tech/Innovation Experts: Promote technology and its benefits (e.g., automation,
augmentation, work de-intensification).
2. Authors/Journalists: Frame narratives to inform or provoke debate, worrying tech
would hurt society (exterminism and job destruction), .
3. Economy/Labor Market Experts: Highlight economic impacts like job loss or
re-upskilling needs, job destruction. Humans can adapt to new jobs.
4. Policymakers/Public Administrators: Propose regulations and policies to
manage these changes.
5. Engaged Citizens: React to narratives, often voicing concerns (e.g., loss of
privacy, inequality).
These Narratives Matter
● Political Nature: Narratives are not neutral predictions; they reflect political and
ideological struggles over what the future should look like.
● Influence on Reality: Dominant narratives influence societal actions and policies,
shaping the future (e.g., funding for upskilling programs).
● Second-Order Chaos: Predictions about the future influence the outcome itself.
○ Example: If people believe AI will replace jobs, it can accelerate decisions to automate.
The truth is not out there: An enacted view of the digital economy. In:
Understanding the digital economy: Data, tools, and research. Orlikowski, W.
J., & Iacono, C. S. (2000).
3 approaches
1. Technological determinism
2. Strategic choice
3. Enacted view
1. Technological Determinism
, Technology is a neutral, exogenous (dıştan kaynaklı) force that exerts unidirectional
and causal influences over humans and organizations. Similar to those operating in
nature.
Tech is an object that influences organizational outcomes such as: increasing
productivity, expanding collaboration, leading decentralization…
2. Strategic Choice
Managers decide which technologies they will adopt through strategic alignment of
the tech with the organization. This choice determines the outcome, not the tech
itself.
Managers rather than users are the key actors in shaping technology to a
particular organizational or economic end.
3. Enacted View
Ongoing technological production: tech is center stage.
Outcomes emerge from our situated actions (practices), and collective actions,
Recognize the social and unpredictable nature of technological use.
3 implications
- tech is social, dynamic, and multiple
- tech must be used to have an effect
- use of tech has unintended consequences
(Volti 2012) Professionals and professionlization
This paper, titled "Professions and Professionalization" by Rudi Volti (2012),
discusses the distinct characteristics of professions, how they differ from other
occupations, and the process of professionalization.
Key Points:
1. Definition of a Profession: A profession is marked by specialized
knowledge, formal education, and adherence to ethical standards.
Professions such as medicine and law hold a higher status compared to other
occupations because of their unique roles and responsibilities in society.
